title: Drusen quantification for early identification of age related macular degeneration (AMD) using color fundus imaging.
abstract: Age-related macular degeneration (AMD) is a major cause of visual impairment in the elderly and identifying people with the early stages of AMD is important when considering the design and implementation of preventative strategies for late AMD. Quantification of drusen size and total area covered by drusen is an important risk factor for progression. In this paper, we propose a method to detect drusen and quantify drusen size along with the area covered with drusen in macular region from standard color retinal images. We used combined local intensity distribution, adaptive intensity thresholding and edge information to detect potential drusen areas. The proposed method detected the presence of any drusen with 100% accuracy (50/50 images). For drusen detection accuracy (DDA), the segmentations produced by the automated method on individual images achieved mean sensitivity and specificity values of 74.94% and 81.17%, respectively.
authors.forename: Alauddin
authors.initials: A
authors.lastname: Bhuiyan
authors.forename: C
authors.initials: C
authors.lastname: Karmakar
authors.forename: Di
authors.initials: D
authors.lastname: Xiao
authors.forename: Kotagiri
authors.initials: K
authors.lastname: Ramamohanarao
authors.forename: Yogi
authors.initials: Y
authors.lastname: Kanagasingam
mesh_terms: D000368:Aged; D003116:Color; D003952:Diagnostic Imaging / Q000295:instrumentation* / Q000379:methods; D005654:Fundus Oculi; D006801:Humans; D008268:Macular Degeneration / Q000175:diagnosis*; D008875:Middle Aged; D016011:Normal Distribution; D015588:Observer Variation; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D015593:Retinal Drusen / Q000175:diagnosis*; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012984:Software